Homo moralis: Personal characteristics, institutions, and moral decision-making

This paper studies how individual characteristics, institutions, and their interaction influence moral decisions. We validate a moral paradigm focusing on the willingness to accept harming third parties. Consequences of moral decisions are real. We explore how moral behavior varies with individual characteristics and how these characteristics interact with market institutions compared to situations of individual decision-making. Intelligence, female gender, and the existence of siblings positively influence moral decisions, in individual and in market environments. Yet in markets, most personalities tend to follow overall much lower moral standards. Only fluid intelligence specifically counteracts moral-eroding effects of markets

Tuberculosis Disease Detection through CXR Images based on Deep Neural Network Approach

Tuberculosis (TB) is a disease that, if left untreated for an extended period of time, can ultimately be fatal. Early TB detection can be aided by using a deep learning ensemble. In previous work, ensemble classifiers were only trained on images that shared similar characteristics. It is necessary for an ensemble to produce a diverse set of errors in order for it to be useful; this can be accomplished by making use of a number of different classifiers and/or features. In light of this, a brand-new framework has been constructed in this study for the purpose of segmenting and identifying TB in human Chest X-ray. It was determined that searching traditional web databases for chest X-ray was necessary. At this point, we pass the photos that we have collected over to Swin ResUnet3 so that they may be segmented. After the segmented chest X-ray have been provided to it, the Multi-scale Attention-based Densenet with Extreme Learning Machine (MAD-ELM) model will be applied in the detection stage in order to effectively diagnose tuberculosis from human chest X-ray. This will be done in order to maximize efficiency. Because it increased the variety of errors made by the basic classifiers, the supplied variation of the approach that was proposed was able to detect tuberculosis more effectively. The proposed ensemble method produced results with an accuracy of 94.2 percent, which are comparable to those obtained by past efforts

Users' trust in information resources in the Web environment: a status report

This study has three aims; to provide an overview of the ways in which trust is either assessed or asserted in relation to the use and provision of resources in the Web environment for research and learning; to assess what solutions might be worth further investigation and whether establishing ways to assert trust in academic information resources could assist the development of information literacy; to help increase understanding of how perceptions of trust influence the behaviour of information users

mGPT: Few-Shot Learners Go Multilingual

Recent studies report that autoregressive language models can successfully solve many NLP tasks via zero- and few-shot learning paradigms, which opens up new possibilities for using the pre-trained language models. This paper introduces two autoregressive GPT-like models with 1.3 billion and 13 billion parameters trained on 60 languages from 25 language families using Wikipedia and Colossal Clean Crawled Corpus. We reproduce the GPT-3 architecture using GPT-2 sources and the sparse attention mechanism; Deepspeed and Megatron frameworks allow us to parallelize the training and inference steps effectively. The resulting models show performance on par with the recently released XGLM models by Facebook, covering more languages and enhancing NLP possibilities for low resource languages of CIS countries and Russian small nations. We detail the motivation for the choices of the architecture design, thoroughly describe the data preparation pipeline, and train five small versions of the model to choose the most optimal multilingual tokenization strategy. We measure the model perplexity in all covered languages and evaluate it on the wide spectre of multilingual tasks, including classification, generative, sequence labeling and knowledge probing. The models were evaluated with the zero-shot and few-shot methods. Furthermore, we compared the classification tasks with the state-of-the-art multilingual model XGLM. source code and the mGPT XL model are publicly released

"It's All Part of an Education": Case Studies of Writing Knowledge Transfer Across Academic and Social Media Domains Among Four Feminist College Students

This dissertation consists of four micro-case studies of intersectional feminist college students’ experiences with writing across digital extracurricular and academic domains. These micro-case studies were selected from a longitudinal study of eight students’ experiences. In response to ongoing questions about writing knowledge transfer generally and transfer between online and academic contexts more specifically, this study was designed to explore whether and how these writers made connections between digital extracurricular and academic contexts of writing. Data collection consisted of four interviews with eight participants over the course of two years and the ongoing collection of academic and online writing samples over the course of one academic year. Through the analysis of interview data, I present two main types of learning transfer across domains; the first type of learning transfer is also supported by analysis of students’ online writing. Through these micro-case studies, I shed light on two previously under-explored types of writing knowledge transfer across these domains, moving in both directions: the transfer (and transformation) of genre knowledge from academic contexts into digital extracurricular contexts, and the transfer of content knowledge forged through online reading into academic writing assignments. Participants in this study tended to confirm previous research suggesting that students generally compartmentalize their writing knowledge across these two domains. I illustrate this trend through a case study of a particularly salient example of such compartmentalization provided by the experiences of one participant, Nora. However, among the experiences of the four participants who served as focal cases for the analysis I present in this dissertation, there were two main exceptions to the compartmentalization trend. For example, in response to unprecedented online rhetorical situations, three participants in this study reported selecting and transforming prior academic genre knowledge by infusing it with multimodal elements to meet the demands of the new rhetorical situation. This cluster of findings suggests a previously unexplored relationship between antecedent genre uptake as articulated by Angela Rounsaville (2012), and what Kara Poe Alexander, Michael-John DePalma, and Jeffrey Ringer (2016) term “adaptive remediation,” thus putting in conversation two previously separate theories of writing knowledge transfer. Additionally, when faced with open-ended writing assignments in unfamiliar disciplines in the humanities and social sciences, all participants reported drawing on their expertise in intersectional feminism, forged in the digital extracurriculum, as a means of locating topics for academic writing assignments. Through two micro-case studies of writers enacting this strategy, I explore the relationship between reading, content knowledge, and writing knowledge transfer, an area that is as yet under-explored in the writing knowledge transfer literature. Together, these two sets of findings suggest that in some cases undergraduate writers may transfer writing knowledge across online and academic domains, and that they can demonstrate considerable resourcefulness when doing so: when faced with an unprecedented, unfamiliar, or ill-defined rhetorical situation in one domain, four participants in this study drew on resources from another domain (e.g., academic genre knowledge; extracurricular content knowledge) in order to support their performance. These participants’ experiences reinforce models of writing knowledge transfer that emphasize adaptation or transformation, and they also suggest that more sustained attention should be paid to the roles of digital extracurricular writing, multimodal composition, and reading in future transfer research.PHDEnglish & EducationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146004/1/aknutson_1.pd

PROGRAM and PROCEEDINGS THE NEBRASKA ACADEMY OF SCIENCES: 139th Anniversary Year, One Hundred-Twenty-Ninth Annual Meeting, April 12, 2019, NEBRASKA WESLEYAN UNIVERSITY, LINCOLN, NEBRASKA

PROGRAM AT-A-GLANCE FRIDAY, APRIL 12, 2019 7:30 a.m. REGISTRATION OPENS - Lobby of Lecture Wing, Olin Hall 8:00 Aeronautics and Space Science, Session A – Acklie 109 Aeronautics and Space Science, Session B – Acklie 111 Collegiate Academy; Biology, Session B - Olin B Biological and Medical Sciences, Session A - Olin 112 Biological and Medical Sciences, Session B - Smith Callen Conference Center Chemistry and Physics; Chemistry - Olin A 8:00 “Teaching and Learning the Dynamics of Cellular Respiration Using Interactive Computer Simulations” Workshop – Olin 110 9:30 “Life After College: Building Your Resume for the Future” Workshop – Acklie 218 8:25 Collegiate Academy; Chemistry and Physics, Session A – Acklie 007 8:36 Collegiate Academy; Biology, Session A - Olin 111 9:00 Chemistry and Physics; Physics – Acklie 320 9:10 Aeronautics and Space Science, Poster Session – Acklie 109 & 111 10:30 Aeronautics and Space Science, Poster Session – Acklie 109 & 111 11:00 MAIBEN MEMORIAL LECTURE: Dr David Swanson - OLIN B Scholarship and Friend of Science Award announcements 12:00 p.m. LUNCH – WESLEYAN CAFETERIA Round-Table Discussion – “Assessing the Academy: Current Issues and Avenues for Growth” led by Todd Young – Sunflower Room 12:50 Anthropology – Acklie 109 1:00 Applied Science and Technology - Olin 111 Biological and Medical Sciences, Session C - Olin 112 Biological and Medical Sciences, Session D - Smith Callen Conference Center Chemistry and Physics; Chemistry - Olin A Collegiate Academy; Biology, Session B - Olin B Earth Science – Acklie 007 Environmental Sciences – Acklie 111 Teaching of Science and Math – Acklie 218 1:20 Chemistry and Physics; Physics – Acklie 320 4:30 BUSINESS MEETING - OLIN B NEBRASKA ASSOCIATION OF TEACHERS OF SCIENCE (NATS) The 2019 Fall Conference of the Nebraska Association of Teachers of Science (NATS) will be held at the Younes Conference Center, Kearney, NE, September 19-21, 2019. President: Betsy Barent, Norris Public Schools, Firth, NE President-Elect: Anya Covarrubias, Grand Island Public Schools, Grand Island, NE AFFILIATED SOCIETIES OF THE NEBRASKA ACADEMY OF SCIENCES, INC. 1. American Association of Physics Teachers, Nebraska Section Web site: http://www.aapt.org/sections/officers.cfm?section=Nebraska 2. Friends of Loren Eiseley Web site: http://www.eiseley.org/ 3. Lincoln Gem & Mineral Club Web site: http://www.lincolngemmineralclub.org/ 4. Nebraska Chapter, National Council for Geographic Education 5. Nebraska Geological Society Web site: http://www.nebraskageologicalsociety.org Sponsors of a $50 award to the outstanding student paper presented at the Nebraska Academy of Sciences Annual Meeting, Earth Science /Nebraska Chapter, Nat\u27l Council Sections 6. Nebraska Graduate Women in Science 7. Nebraska Junior Academy of Sciences Web site: http://www.nebraskajunioracademyofsciences.org/ 8. Nebraska Ornithologists’ Union Web site: http://www.noubirds.org/ 9. Nebraska Psychological Association http://www.nebpsych.org/ 10. Nebraska-Southeast South Dakota Section Mathematical Association of America Web site: http://sections.maa.org/nesesd/ 11. Nebraska Space Grant Consortium Web site: http://www.ne.spacegrant.org